Research on AUV Allocation Method Based on Optimization Algorithm

Zhang Hongqiang, Zeng Bin, Kang Jian
{"title":"Research on AUV Allocation Method Based on Optimization Algorithm","authors":"Zhang Hongqiang, Zeng Bin, Kang Jian","doi":"10.1109/CBFD52659.2021.00061","DOIUrl":null,"url":null,"abstract":"With the development of science and technology, the performance of autonomous underwater vehicles (AUV) has been continuously improved, and its application has become increasingly widespread, playing an important role in the military and civilian fields. AUV can perform underwater environmental reconnaissance, resource exploration, target search, and intelligence collection. In order to efficiently complete reconnaissance and search tasks, AUV resources need to be allocated scientifically and reasonably. Due to the complex underwater environment, the robustness in the search process should be considered for many influencing factors. Considering Using multiple AUVs to search multiple target areas, In this paper, an improved genetic algorithm is used for task allocation, and then the simulated annealing algorithm is used to plan the shortest path with reference to the multiple traveling salesman problem. The two algorithms are improved to improve the convergence speed, and finally use Matlab to simulate Verify the effectiveness of the improved algorithm.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBFD52659.2021.00061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

With the development of science and technology, the performance of autonomous underwater vehicles (AUV) has been continuously improved, and its application has become increasingly widespread, playing an important role in the military and civilian fields. AUV can perform underwater environmental reconnaissance, resource exploration, target search, and intelligence collection. In order to efficiently complete reconnaissance and search tasks, AUV resources need to be allocated scientifically and reasonably. Due to the complex underwater environment, the robustness in the search process should be considered for many influencing factors. Considering Using multiple AUVs to search multiple target areas, In this paper, an improved genetic algorithm is used for task allocation, and then the simulated annealing algorithm is used to plan the shortest path with reference to the multiple traveling salesman problem. The two algorithms are improved to improve the convergence speed, and finally use Matlab to simulate Verify the effectiveness of the improved algorithm.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于优化算法的水下航行器分配方法研究
随着科学技术的发展,自主水下航行器(AUV)的性能不断提高,其应用日益广泛,在军事和民用领域发挥着重要作用。AUV可以执行水下环境侦察、资源勘探、目标搜索和情报收集等任务。为了高效地完成侦察和搜索任务,需要对水下航行器资源进行科学合理的配置。由于水下环境复杂,搜索过程中的鲁棒性需要考虑多种影响因素。考虑到使用多个auv搜索多个目标区域,本文采用改进的遗传算法进行任务分配,然后参照多旅行商问题,采用模拟退火算法规划最短路径。对两种算法进行了改进,提高了收敛速度,最后用Matlab仿真验证了改进算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
An infrared dim and small target image preprocessing algorithm based on improved bilateral filtering A systematic Analysis: Molecular Information in viral Disease using Deep Learning Auto Encoder Double-Triplet-Pseudo-Siamese Architecture For Remote Sensing Aircraft Target Recognition Improvement of Internal Control of Anti Money Laundering in State-owned Enterprises Based on Evolutionary Game Analysis Forecast on Shanghai Composite Index linked with Investor Sentiment Effect
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1